Difference between revisions of "CSE 7300 Research Seminar"

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* '''Theme: AI for Health'''
 
* '''Instructor''': [http://www.cse.wustl.edu/~lu Prof. Chenyang Lu]
 
* '''Instructor''': [http://www.cse.wustl.edu/~lu Prof. Chenyang Lu]
−
* '''Semester''': Fall 2020
+
* '''Semester''': '''Fall 2024'''
−
* '''Time''': Thursday at 4pm-4:50pm
+
* '''Time''': Wednesday at 1 PM
−
* '''Location''': Virtual
+
* '''Location''': McKelvey 1030
 +
* '''[http://www.cse.wustl.edu/~lu/talks/seminar_guidelines.pdf Guidelines]''':  
 +
* '''Recommended sources:''' NeurIPS ([http://nips.cc/]), ICML ([http://icml.cc/]), AAAI ([http://www.aaai.org/]), SIGKDD ([http://www.kdd.org/]), IJCAI ([http://www.ijcai.org/]), IMWUT ([http://dl.acm.org/journal/imwut]), HEALTH ([http://dl.acm.org/journal/health]), Digital Medicine ([http://www.nature.com/npjdigitalmed/]), Lancet Digital Health ([https://www.thelancet.com/journals/landig/issues#decade=loi_decade_201]), NEJM AI ([https://ai.nejm.org/])
  
 +
==Presentation Schedule==
  
−
=== ---ML for Health ---===
+
=== ---Sep 11 ---===
 +
Ziqi
  
−
* NeurIPS ([http://nips.cc/])
+
Gawlikowski, J., Tassi, C.R.N., Ali, M. et al. A survey of uncertainty in deep neural networks. Artif Intell Rev 56 (Suppl 1), 1513–1589 (2023). [https://doi.org/10.1007/s10462-023-10562-9]
−
* ICML ([http://icml.cc/])
 
−
* AAAI ([http://www.aaai.org/])
 
−
* SIGKDD ([http://www.kdd.org/])
 
−
* IJCAI ([http://www.ijcai.org/])
 
−
* IMWUT ([http://dl.acm.org/journal/imwut])
 
−
* Digital Medicine ([http://www.nature.com/npjdigitalmed/])
 
−
* HEALTH ([http://dl.acm.org/journal/health])
 
−
* Lancet Digital Health ([https://www.thelancet.com/journals/landig/issues#decade=loi_decade_201])
 
  
−
=== ---Cyber Physical Systems ---===
+
=== ---Sep 18 ---===
 +
Daoyi
  
−
* SenSys ([http://sensys.acm.org])
+
Hüyük, A., Wei, Q., Curth, A. and van der Schaar, M., 2024. Defining Expertise: Applications to Treatment Effect Estimation. arXiv preprint arXiv:2403.00694. [https://openreview.net/pdf?id=1YPfmglNRU]
−
* IPSN ([http://ipsn.acm.org])
 
−
* RTSS ([http://www.rtss.org/])
 
−
* RTAS ([http://www.rtas.org/])
 
−
* ICCPS ([http://www.iccps.org])
 
−
* MobiCom ([https://sigmobile.org/mobicom/2019/])
 
−
* MobiSys ([http://www.sigmobile.org/mobisys/2019/])
 
−
* Sigcomm ([http://conferences.sigcomm.org/sigcomm/2019/])
 
−
* NSDI ([https://www.usenix.org/conference/nsdi19])
 
−
* SOSP ([https://www.sigops.org/])
 
−
* OSDI ([https://www.usenix.org/conference/osdi18/])
 
  
−
=== ---Oct 1 ---===
+
=== ---Sep 25 ---===
 +
Jason
  
−
Jingwen
+
Park, C., Awadalla, A., Kohno, T., & Patel, S. (2021). Reliable and Trustworthy Machine Learning for Health Using Dataset Shift Detection. In M. Ranzato, A. Beygelzimer, Y. Dauphin, P. S. Liang, & J. W. Vaughan (Eds.), Advances in Neural Information Processing Systems (Vol. 34, pp. 3043–3056).
 +
[https://proceedings.neurips.cc/paper_files/paper/2021/file/17e23e50bedc63b4095e3d8204ce063b-Paper.pdf]
  
−
Paper: Goldstein, Orpaz, et al. "Target-Focused Feature Selection Using Uncertainty Measurements in Healthcare Data." ACM Transactions on Computing for Healthcare 1.3 (2020): 1-17. [https://dl.acm.org/doi/10.1145/3383685]
+
=== ---Oct 02 ---===
 +
Ben
  
−
=== ---Oct 8 ---===
+
Bick, A., Li, K.Y., Xing, E.P., Kolter, J.Z. and Gu, A., 2024. Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models. arXiv preprint arXiv:2408.10189. [https://arxiv.org/pdf/2408.10189]
  
−
Ruixuan
+
Dao, T. and Gu, A., 2024. Transformers are SSMs: Generalized models and efficient algorithms through structured state space duality. arXiv preprint arXiv:2405.21060. [https://arxiv.org/pdf/2405.21060]
  
−
Wiens, Jenna, John Guttag, and Eric Horvitz. "A study in transfer learning: leveraging data from multiple hospitals to enhance hospital-specific predictions." Journal of the American Medical Informatics Association 21.4 (2014): 699-706.
+
=== ---Oct 09 ---===
−
[https://academic.oup.com/jamia/article/21/4/699/761441]
+
Claire
  
−
=== ---Oct 15 ---===
+
Qian Z, Zhang Y, Bica I, Wood A, van der Schaar M. Synctwin: Treatment effect estimation with longitudinal outcomes. Advances in Neural Information Processing Systems. 2021 Dec 6;34:3178-90. [https://proceedings.neurips.cc/paper_files/paper/2021/file/19485224d128528da1602ca47383f078-Paper.pdf]
  
−
Hanyang
+
=== ---Oct 16 ---===
 +
Wenyu
  
−
Bianchi, Filippo Maria, et al. "Learning representations of multivariate time series with missing data." Pattern Recognition 96 (2019): 106973.https://arxiv.org/abs/1805.03473
+
Nouha Dziri, Ximing Lu, Melanie Sclar, Xiang Lorraine Li, Liwei Jiang, Bill Yuchen Lin, Peter West, Chandra Bhagavatula, Ronan Le Bras, Jena D. Hwang, Soumya Sanyal, Sean Welleck, Xiang Ren, Allyson Ettinger, Zaid Harchaoui, and Yejin Choi. 2024. Faith and fate: limits of transformers on compositionality. In Proceedings of the 37th International Conference on Neural Information Processing Systems (NIPS '23). Curran Associates Inc., Red Hook, NY, USA, Article 3081, 70293–70332.
 +
[https://dl.acm.org/doi/10.5555/3666122.3669203]
  
−
AAAI’20, A Kernel to Exploit Informative Missingness in Multivariate Time Series from EHRs. https://arxiv.org/abs/2002.12359
+
=== ---Oct 23 ---===
 +
Di
  
−
=== ---Oct 22 ---===
+
Xu, Shusheng, Wei Fu, Jiaxuan Gao, Wenjie Ye, Weilin Liu, Zhiyu Mei, Guangju Wang, Chao Yu, and Yi Wu. "Is dpo superior to ppo for llm alignment? a comprehensive study." arXiv preprint arXiv:2404.10719 (2024). [https://arxiv.org/pdf/2404.10719]
  
−
Cancel (SIGMETRICS/IoTDI/RTAS)
+
=== ---Oct 30 ---===
 +
Behrooz
  
−
=== ---Oct 29 ---===
+
Renc, Pawel, Yugang Jia, Anthony E. Samir, Jaroslaw Was, Quanzheng Li, David W. Bates, and Arkadiusz Sitek. "Zero shot health trajectory prediction using transformer." NPJ Digital Medicine 7, no. 1 (2024): 256. [https://www.nature.com/articles/s41746-024-01235-0]
  
−
Cancel
+
=== ---Nov 06 ---===
 +
Prince
  
−
=== ---Nov 5---===
+
Fan, Na, Zeyue Tian, Amartansh Dubey, Samruddhi Deshmukh, Ross Murch, and Qifeng Chen. "Multitarget Device-Free Localization via Cross-Domain Wi-Fi RSS Training Data and Attentional Prior Fusion." In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 38, no. 1, pp. 91-99. 2024. [https://ojs.aaai.org/index.php/AAAI/article/view/27759]
  
−
Liang
+
=== ---Nov 13 ---===
 +
Prince
  
−
Paper: Mangaokar, Neal, Jiameng Pu, Parantapa Bhattacharya, Chandan K. Reddy, and Bimal Viswanath. "Jekyll: Attacking Medical Image Diagnostics using Deep Generative Models." [https://people.cs.vt.edu/vbimal/publications/jekyll-eurosp20.pdf]
+
Fan, Na, Zeyue Tian, Amartansh Dubey, Samruddhi Deshmukh, Ross Murch, and Qifeng Chen. "Multitarget Device-Free Localization via Cross-Domain Wi-Fi RSS Training Data and Attentional Prior Fusion." In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 38, no. 1, pp. 91-99. 2024. [https://ojs.aaai.org/index.php/AAAI/article/view/27759]
  
−
=== ---Nov 12---===
 
  
−
Bing
+
=== ---Nov 20 ---===
−
 
+
Peiqi
−
Grabocka, Josif, et al. "Learning time-series shapelets." Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining. 2014.
 
−
 
 
−
Ye, Lexiang, and Eamonn Keogh. "Time series shapelets: a new primitive for data mining." Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining. 2009.
 
−
 
 
−
=== ---Nov 19---===
 
−
 
 
−
Saumik
 
−
 
 
−
Paper: Jiao, York, et al. "Probabilistic forecasting of surgical case duration using machine learning: model development and validation." Journal of the American Medical Informatics Association (2020).
 
−
 
 
−
=== ---Nov 26---===
 
  
 +
=== ---Nov 27 ---===
 
Thanksgiving
 
Thanksgiving
  
−
=== ---Dec 3---===
 
−
 
−
Jingwen
 
−
 
−
Literature review about contact tracing
 
−
 
−
=== ---Dec 10---===
 
−
 
−
Hanyang
 
−
 
−
Cao, Bokai, et al. "Deepmood: modeling mobile phone typing dynamics for mood detection." KDD. 2017.
 
−
https://dl.acm.org/doi/pdf/10.1145/3097983.3098086
 
−
 
−
=== ---Dec 17---===
 
−
 
−
Liang
 
−
 
−
Choi, Edward, et al. "Doctor ai: Predicting clinical events via recurrent neural networks." Machine Learning for Healthcare Conference. 2016. [http://proceedings.mlr.press/v56/Choi16.pdf]
 
  
 
==Previous Semesters==
 
==Previous Semesters==
 +
* [[Seminar Spring 2024|Spring 2024]]
 +
* [[Seminar Fall 2023|Fall 2023]]
 +
* [[Seminar Spring 2023|Spring 2023]]
 +
* [[Seminar Fall 2022|Fall 2022]]
 +
* [[Seminar Summer 2022|Summer 2022]]
 +
* [[Seminar Spring 2022|Spring 2022]]
 +
* [[Seminar Fall 2021|Fall 2021]]
 +
* [[Seminar Summer 2021|Summer 2021]]
 +
* [[Seminar Spring 2021|Spring 2021]]
 +
* [[Seminar Fall 2020|Fall 2020]]
 +
* [[Seminar Summer 2020|Summer 2020]]
 
* [[Seminar Spring 2020|Spring 2020]]
 
* [[Seminar Spring 2020|Spring 2020]]
 
* [[Seminar Fall 2019|Fall 2019]]
 
* [[Seminar Fall 2019|Fall 2019]]

Latest revision as of 19:23, 6 November 2024

  • Theme: AI for Health
  • Instructor: Prof. Chenyang Lu
  • Semester: Fall 2024
  • Time: Wednesday at 1 PM
  • Location: McKelvey 1030
  • Guidelines:
  • Recommended sources: NeurIPS ([1]), ICML ([2]), AAAI ([3]), SIGKDD ([4]), IJCAI ([5]), IMWUT ([6]), HEALTH ([7]), Digital Medicine ([8]), Lancet Digital Health ([9]), NEJM AI ([10])

Presentation Schedule

---Sep 11 ---

Ziqi

Gawlikowski, J., Tassi, C.R.N., Ali, M. et al. A survey of uncertainty in deep neural networks. Artif Intell Rev 56 (Suppl 1), 1513–1589 (2023). [11]

---Sep 18 ---

Daoyi

Hüyük, A., Wei, Q., Curth, A. and van der Schaar, M., 2024. Defining Expertise: Applications to Treatment Effect Estimation. arXiv preprint arXiv:2403.00694. [12]

---Sep 25 ---

Jason

Park, C., Awadalla, A., Kohno, T., & Patel, S. (2021). Reliable and Trustworthy Machine Learning for Health Using Dataset Shift Detection. In M. Ranzato, A. Beygelzimer, Y. Dauphin, P. S. Liang, & J. W. Vaughan (Eds.), Advances in Neural Information Processing Systems (Vol. 34, pp. 3043–3056). [13]

---Oct 02 ---

Ben

Bick, A., Li, K.Y., Xing, E.P., Kolter, J.Z. and Gu, A., 2024. Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models. arXiv preprint arXiv:2408.10189. [14]

Dao, T. and Gu, A., 2024. Transformers are SSMs: Generalized models and efficient algorithms through structured state space duality. arXiv preprint arXiv:2405.21060. [15]

---Oct 09 ---

Claire

Qian Z, Zhang Y, Bica I, Wood A, van der Schaar M. Synctwin: Treatment effect estimation with longitudinal outcomes. Advances in Neural Information Processing Systems. 2021 Dec 6;34:3178-90. [16]

---Oct 16 ---

Wenyu

Nouha Dziri, Ximing Lu, Melanie Sclar, Xiang Lorraine Li, Liwei Jiang, Bill Yuchen Lin, Peter West, Chandra Bhagavatula, Ronan Le Bras, Jena D. Hwang, Soumya Sanyal, Sean Welleck, Xiang Ren, Allyson Ettinger, Zaid Harchaoui, and Yejin Choi. 2024. Faith and fate: limits of transformers on compositionality. In Proceedings of the 37th International Conference on Neural Information Processing Systems (NIPS '23). Curran Associates Inc., Red Hook, NY, USA, Article 3081, 70293–70332. [17]

---Oct 23 ---

Di

Xu, Shusheng, Wei Fu, Jiaxuan Gao, Wenjie Ye, Weilin Liu, Zhiyu Mei, Guangju Wang, Chao Yu, and Yi Wu. "Is dpo superior to ppo for llm alignment? a comprehensive study." arXiv preprint arXiv:2404.10719 (2024). [18]

---Oct 30 ---

Behrooz

Renc, Pawel, Yugang Jia, Anthony E. Samir, Jaroslaw Was, Quanzheng Li, David W. Bates, and Arkadiusz Sitek. "Zero shot health trajectory prediction using transformer." NPJ Digital Medicine 7, no. 1 (2024): 256. [19]

---Nov 06 ---

Prince

Fan, Na, Zeyue Tian, Amartansh Dubey, Samruddhi Deshmukh, Ross Murch, and Qifeng Chen. "Multitarget Device-Free Localization via Cross-Domain Wi-Fi RSS Training Data and Attentional Prior Fusion." In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 38, no. 1, pp. 91-99. 2024. [20]

---Nov 13 ---

Prince

Fan, Na, Zeyue Tian, Amartansh Dubey, Samruddhi Deshmukh, Ross Murch, and Qifeng Chen. "Multitarget Device-Free Localization via Cross-Domain Wi-Fi RSS Training Data and Attentional Prior Fusion." In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 38, no. 1, pp. 91-99. 2024. [21]


---Nov 20 ---

Peiqi

---Nov 27 ---

Thanksgiving


Previous Semesters

Previous Lab Meetings

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